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Reposted by Lukas Gunschera

🎃 public HELLth guy 🎃 @publichealthguy1.bsky.social · 1d

they just slapped a surgeons general warning on RFK like he’s a pack of cigarettes

Dan Diamond @ddiamond.bsky.social · 1d

“Secretary Kennedy is entitled to his views. But he is not entitled to put people’s health at risk.”

Six former surgeons general condemn RFK Jr.

Opinion | Six surgeons general: RFK Jr. is a threat to the health of Americans

It was our duty in office to warn of dangers when we found them. We’re doing that again today.

www.washingtonpost.com

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Reposted by Lukas Gunschera

samuel mehr @mehr.nz · 28d

psych departments post a faculty job that has nothing to do with AI challenge

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doctor eek [free link arc] (alt decorative gourd season) @absolutely-not.bsky.social · 6d

i looked at the methodology for this and it is
a. sex addiction counseling group in texas did a surveymonkey and extrapolated the results to the entire us population which is the sort of research design that earns you an ff on an intro methods class (the extra f is for extra effort), and
b. p-hacked

The Independent @the-independent.com · 6d

Nearly a third of Americans have had a ‘romantic relationship’ with an AI bot, new survey says

1 in 3 Americans have had a ‘romantic relationship’ with an AI bot, new survey says

www.independent.co.uk

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Julia M. Rohrer @dingdingpeng.the100.ci · 8d

A lot of psych is already conducted with online convenience samples & ppl are probably excited about silicon samples bc it would allow them to crank out more studies for even less 💸

How about we reconsider the idea that sciencey science involves collecting own data.
www.science.org/content/arti...

AI-generated ‘participants’ can lead social science experiments astray, study finds

Data produced by “silicon samples” depends on researchers’ exact choice of models, prompts, and settings

www.science.org

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Lukas Gunschera @lukasgunschera.com · 8d

Slides are available at www.rcpsych.ac.uk/events/confe...

Faculty of Child and Adolescent Psychiatry Annual Conference 2025 - conference resources

Full details of the event, including abstracts, speaker biographies and slides.

www.rcpsych.ac.uk

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Simon Ciranka @simyciri.bsky.social · 10d

😍 Our latest is out now in @commspsychol.nature.com. 🤩 We show with Bayesian modelling and experimental manipulation of uncertainty that developmental differences in social influence depend on differences in the internal uncertainty people have about their choice
doi.org/10.1038/s442...

Internal uncertainty impacts social information use in risky choice across adolescence - Communications Psychology

Adolescents’ choices are influenced by others. A social risky choice experiment and Bayesian modelling reveal that age differences in internal uncertainty, being unsure how to choose, relate to differences in susceptibility to social influence.

doi.org

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Diane Coyle @dianecoyle1859.bsky.social · 10d

on.ft.com/46EDjIX Europe’s bill for extreme weather damage more than doubles this decade (2020-23 costs already more than double previous 10 years - good thing financial markets are so forward-looking. Oh)

Europe’s bill for extreme weather damage more than doubles this decade

Average economic losses associated with weather including intense floods have soared, according to European agency

on.ft.com

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Lukas Gunschera @lukasgunschera.com · 12d

Grateful to @rcpsych.bsky.social for the opportunity to present my research on “Rethinking social media addiction” and participate in the panel discussion.

Looking forward to translating the insights into the clinical-focused work in the pipeline.

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Lukas Gunschera @lukasgunschera.com · 13d

Huge congratulations!🎊 @emilyanntowner.bsky.social

Lukas Gunschera @lukasgunschera.com · 13d

Reposting twice because it's such a great read!

Sara Mehrhof @saramehrhof.bsky.social · 13d

Mental and metabolic health are closely linked - but what drives this connection? In our new theory paper, we (w/ @camillanord.bsky.social & @hugofleming.bsky.social g.bsky.social) propose dysregulation of interoceptive energy allostasis as a key mechanism.
www.science.org/doi/10.1126/... 🧵 1/n

An interoceptive model of energy allostasis linking metabolic and mental health

Interactions between metabolic interoception and regulation may drive comorbidity between mental and metabolic ill-health.

www.science.org

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Reposted by Lukas Gunschera

Camilla Nord @camillanord.bsky.social · 13d

What drives the bidirectional relationship between metabolic and mental ill-health?

Read our new metabolic psychiatry paper, “An interoceptive model of energy allostasis linking metabolic and mental health” www.science.org/doi/10.1126/... led by @saramehrhof.bsky.social @hugofleming.bsky.social

An interoceptive model of energy allostasis linking metabolic and mental health

Interactions between metabolic interoception and regulation may drive comorbidity between mental and metabolic ill-health.

www.science.org

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Reposted by Lukas Gunschera

Jamie Cummins @jamiecummins.bsky.social · 21d

Can large language models stand in for human participants?
Many social scientists seem to think so, and are already using "silicon samples" in research.

One problem: depending on the analytic decisions made, you can basically get these samples to show any effect you want.

THREAD 🧵

The threat of analytic flexibility in using large language models to simulate human data: A call to attention

Social scientists are now using large language models to create "silicon samples" - synthetic datasets intended to stand in for human respondents, aimed at revolutionising human subjects research. How...

arxiv.org

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Lukas Gunschera @lukasgunschera.com · 22d

Excited to see this brilliant work from @bcdavidson.bsky.social preprinted! Check it out at osf.io/preprints/ps...

Brandon C Davidson @bcdavidson.bsky.social · 22d

🚨 New Preprint 🚨

Prolonged Isolation is associated with an increased behavioural sensitivity to ‘Likes’ on social media.

🧵

Social media rewards are inherently social—but does posting change during social isolation, when in-person social rewards are limited?

It turns out, yes!

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Johnny Ryan @johnnyryan.bsky.social · Sep 1

If true, this update is astonishing.
The Commission climbed down from a planned break up of Google’s ad business to a mere fine, and then dropped even the fine for fear of offending Trump.

This is for market violations that have been proven in U.S. court.

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Morgan Robertson @morganrobertson.bsky.social · Aug 31

Important reading as you prepare for your semester

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Julia M. Rohrer @dingdingpeng.the100.ci · Aug 25

Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...

Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities

Abstract
Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).

Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.

A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals).

Illustrated are
1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals
2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and
3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.

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Reposted by Lukas Gunschera

Daniel Lakens @lakens.bsky.social · Aug 25

If you are preparing your bachelor statistics course and would like to add optional material for students to better understand statistics on a conceptual level (see topics in the screenshot) my free textbook provides a state of the art overview. lakens.github.io/statistical_...

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Nils Kroemer @nbkroemer.bsky.social · Aug 19

Do researchers’ financial conflicts of interest in clinical trials of internet-based interventions for depression affect the outcomes? This meta-analysis suggests that COIs may lead to inflated effect-size estimates. 🩺 #neuroskyence
www.tandfonline.com/doi/full/10....

Forest plot of the effects of self-guided IBI for depression versus passive control group in trials for which RFCOI was present versus absent or unclear. Studies with RFCOI show larger effects.

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Reposted by Lukas Gunschera

Sam Gershman @gershbrain.bsky.social · Aug 4

A landmark volume, The Handbook of Dopamine, is now online:
www.sciencedirect.com/handbook/han...

Big kudos to the editors, Stephanie Cragg and Mark Walton, for putting this together.

Handbook of Behavioral Neuroscience | Volume 32: The Handbook of Dopamine | ScienceDirect.com by Elsevier

Read the latest chapters of Handbook of Behavioral Neuroscience at ScienceDirect.com, Elsevier’s leading platform of peer-reviewed scholarly literature

www.sciencedirect.com

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Lukas Gunschera @lukasgunschera.com · Aug 1

Thanks for this great article on an important topic. I want to add that there is more nuance to the debate of behavioural addictions, and research *does* support the claim that dopamine drives addiction in other pleasurable behaviors (i.e. gambling). For example: www.nature.com/articles/npp...

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Tobias Hauser @tobiasuhauser.bsky.social · Jul 17

#CPConf2025 is a wrap - thanks to everyone who made this event so special! @unituebingen.bsky.social @tueneurocampus.bsky.social

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Lukas Gunschera @lukasgunschera.com · Jul 16

Amazing, huge congratulations!!🙌🏼

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Amy Orben @orbenamy.bsky.social · Jul 16

I'm hiring 2+ 2.5-year postdocs over the next few months.

Job 1: looking for someone with deep expertise in computational modelling (reinforcement learning, agent based modelling) on real-world/complex data (closing: 18 August, starting: October-December), www.jobs.cam.ac.uk/job/52059/

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Lukas Gunschera @lukasgunschera.com · Jul 15

So exciting!🙌🏼

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Lukas Gunschera @lukasgunschera.com · Jul 15

Brilliant work by @saramehrhof.bsky.social on shared neurocognitive signatures of psychiatric and metabolic disorder at #cpconf2025

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